The American Board of cardiology (ACC) together with American heart Association (AHA) has ontwikkel’n set of guidelines for the assessment of cardiovascular risk in patients based on eight factors, including age, cholesterol and blood pressure. On average, the system correctly predicts the cases in the people from the crisis with the accuracy of 72.8%. It’s a fairly high accuracy, but Steven van zyl and his team from the University of Nottingham have done differently to make the predictions even better. They have four samebecause algorithm, and then provide them with the data 256 378 thousand British patients. The first System used about 295 thousand records to create its internal models, and then use the rest to check and Refine the results. The results of the work of AI algorithms significantly perform better than the criteria for the SEN/HA, which provides accuracy from 74.5 to 76.4 percent. The tests show that the algorithms of the neural network breaks the results of the current guidance methods AAA/HA 7.6 percent, while the results on 1.6 percent fewer false alarms.
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